AI

Enterprises face an unmanaged crisis of AI agent and MCP server sprawl, characterized by rapid, decentralized proliferation of autonomous agents, protocol connections operating with excessive privilege, opaque execution paths, and identity blind spots.
Absent agent-aware governance, modern enterprises struggle to prevent, detect, or contain multi-hop autonomous exploits, leaving environments vulnerable to lateral movement, shadow collaboration, and unauthorized data exfiltration.
More succinctly, in light of the recent OpenAI/Hugging Face incident, monitoring clearly lags behind agent capability. The tooling to observe what agents are actually doing, in real time, is not yet standard practice, even at the labs building the agents.
To that end, Perplexity AI’s open source numbat offers excellent observability and visibility to supported desktop, CLI, IDE, and gateway agents through local hooks and plugins, OTLP/HTTP logs, and on-disk session artifacts.[1]

Courtesy of TLDR InfoSec Launches & Tools again, another fine discovery in Robert McDermott’s AI Powered Knowledge Graph Generator. Robert’s system takes unstructured text, uses your preferred LLM and extracts knowledge in the form of Subject-Predicate-Object (SPO) triplets, then visualizes the relationships as an interactive knowledge graph.[1]

Protect AI’s OSS portfolio includes tools aimed at improving security of AI/ML software. These tools are meant for a wide range of engineering, security and ML practitioners including developers, security engineers/researchers, ML engineers, LLM engineers and prompt engineers, and data scientists.
Of particular interest in light of model serialization attacks is ModelScan.